Tempo
The track that is displayed in the tempogram on this page is Homicide by Rejecta and Act of Rage. The reason I selected this track is because I wanted to see if the algorithms behind the tempogram could accurately predict the tempo when a track contains “kickrolls”. A kickroll is a pattern made with the kick of the track in the verse which deviates from the standard 4/4 pattern in the measure. I knew that the system could probably accurately predict the tempo of a hardcore track since it has a more steady beat and doesn’t contain as many kickrolls. Therefore I selected this track ,because this is a hardstyle track. Since kickrolls usually don’t fall on the 4 beats in a measure I expected this to be interesting. If you look at the tempogram you can see that it predicts that the song is mainly around the 480 bpm. This isn’t strange since that bpm is two tempo octaves above the actual bpm. You can also see a lot of bright points deviating from the straight line in the choruses and verses. These are mainly the kickrolls and this was what I was hoping to see. Not all kickrolls are visible but one of the most visible ones is around the 60 seconds. Furthermore it is interesting to see that the algorithm recorded the tempo going downward around the 45 seconds where that is actually a synth riff. The last thing that is noteworthy is that turning on the cyclic mode of the tempogram actually made the graph worse, usually it would make the graph more readable.
Introduction
# A tibble: 810 × 6
track.name tempo loudn…¹ energy tempo2 tempo3
<chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Colors - Radio Edit 150. -3.40 0.937 150. 150.
2 Lessons In Love - Headhunterz Remix Radio… 150. -3.86 0.893 150. 150.
3 Never Say Goodbye - Wildstylez Radio Edit 148. -3.41 0.834 148. 148.
4 Year Of Summer - Radio Edit 150. -5.57 0.888 150. 150.
5 Catch Me (feat. Naaz) 145. -3.33 0.916 145. 145.
6 Rockstar (feat. DV8) 128. -5.75 0.973 128. 166.
7 Our Church 150. -3.47 0.957 150. 150.
8 Destiny - Edit 150. -4.63 0.791 150. 150.
9 Home 150. -3.81 0.896 150. 150.
10 Waiting For You - Rebourne Remix 75.0 -3.34 0.974 150. 150.
# … with 800 more rows, and abbreviated variable name ¹loudnessIn this storyboard I will attempt to explain the differences between Hardstyle and Hardcore. The data I will use for this project is my own playlist called “Kasper Hardstyle/core”. In this playlist you can find a combination of the two mentioned genres. There are also some songs which could be categorized in the genre Frenchcore but the percentage of songs that could be identified with that genre is very small in my playlist. The reason I chose this subject is because I am very passionate about these genres. Especially since in my spare time I produce songs in these genres. I will try to create a clear view of the differences of these genres and the first difference I’d like to highlight is the difference in tempo. Hardstyle usually has a bpm ranging from 140 to 165, while Hardcore is a bit quicker, most songs are between the 180 and 220 songs. The differences in bpm in both genres can be explained because of the many subgenres that both genres have. The more melodic or “euphoric” subgenres tend to be slower and less melodic subgenres have faster tempo’s.
In the plot you can see tempo on the x-axis with loudness on the y-axis the tempo, the colour of the data points are determined by energy of the tracks. With this plot I’m trying to see if you can clearly see a difference in the genres when it comes to loudness and if you can really separate the two by just tempo. Both these things are the case. The line in the plot is slowly rising as the bpm increases which means that the tracks are gaining loudness on average. The reason this is interesting is because loudness in the case of these songs can also be interpreted as harshness. The songs that are all the way on the right are normally regarded as very rough and harsh songs. The other fun thing is that around the 160 bpm you can very clearly see that the songs switch from genre.
Unexpected chromagram result
The song I selected for analyzing the chroma is “Warriors 2022 edit” by DRS. The reason I selected this song is because I expected it to have very interesting results since it has sections with only one sound playing. These sounds are in the case of Hardcore and Hardstyle nearly always the kicks. In this song you can see some very clear brightness between 5 seconds and 60 seconds. These bright spots are the vocals of the song. That is the way to recognize the introduction. I expected to see more clear sections in the chromagram, but after listening to the song again while analyzing the chromagram I realized why the sections flow more nicely into eachother than I expected. The reason is that the genres I’m covering in this storyboard tend to use multiple choruses that flow into each other. But if you look closely you can see where the choruses are. An example would be to look at the timeframe 100 seconds to roughly 110 second. In that time you see a brighter bar in the E and F notes. This is because those are the two notes that the kick uses for that duration. So that is one of the sections of the song. By doing the same and looking for bars of lighter colours you can spot the sections of the song. This however is far from what I expected since I expected the chromagram to be emptier with more bright bars at the choruses.
Selfsimilarity matrices part 1
In this part of the storyboard I decided to compare the songs “AEON” By DEEZL and “Ignition” by Spitnoise and Deadly Guns. The type of comparison I’ll be doing is a comparison of a selfsimilarity matrix of both songs. I selected these songs because they fill a similar spot in the genres. Both songs have a very rhythmic first chorus and a more melodic last chorus with returning elements and melodies from the verses. I decided to use timbre for the selfsimilarity matrices because I expected that to return the most interesting results and nice contrast between the genres. Furthermore, the matrices are displayed in beats since that yielded the best results. So let look at the results of both matrices.
The first thing to notice when looking at the matrix of “AEON” is that there is a lot of repetition in the song. There is most noticeable a checkerboard pattern around the 20 seconds, 60 seconds, 125 seconds and in the outro of the song. These checkerboards is the arpegiating melody that plays throughout the entire song. The second very noticeable thing is the bright cross at 40 seconds. This bright cross is the first chorus. As you can see, it is hard to find the structure of the song in this matrix. This is especially the case since the same melody is comprised of the same sounds which played in the verse and the chorus. Now let’s look if these findings are also noticeable in the Hardcore song.
Selfsimilarity matrices part 2
The first thing that struck me when I looked at this matrix is that it seems a lot more structured. So let’s see if that is really the case. This matrix has a lot more apparent boxes and squares in it. In these squares you can see more squares but all the bigger squares seem different from the others. This makes it seem as if in this case you can clearly see the different parts of the song. After listening to the song again it does really seem like the matrix picks up the different sections of the song. The first square which lasts until roughly 70 seconds is the introduction and the first chorus. These sections use a lot of similar sounds and are quite empty. Then after that until 150 seconds, the first verse can be found which transitions into a second chorus with similar sounds again. At last there is a verse and a chorus, however, these are quite different which can be seen by looking at the pattern transition at roughly 170 seconds. Although the verses and choruses are very hard to separate in this matrix, it does represent the changing sounds and timbres of the song nicely.
Euphoric chordogram
The song I used for this analysis is “Together We Grow” by “Vertile”. I wanted to highlight a different side of the genres I selected by looking at a very melodic track which is coincidentally one of my favourite songs. What I expected to see was a very constant pattern since the melody of the song keeps being repeated. The result however surprised me a bit. Even though the melody does not change in the song and the instruments that play the melody also don’t (drastically) change, there are very clearly highlighted areas. The explanation which seems to be the case in my opinion is the reason these sections are very brightly coloured in contrast is because the melody stands out more. Less sounds are playing so the melody has more space and is even the only sound playing sometimes. This is especially the case in the introduction which is why it is so lit up. The last thing that surprised me is that it is impossible to make out which chords are playing in the chordogram. I can’t find a reason for this since in the song it is very clear that a singular chord is playing at a time and the chords are even a bar or multiple bars long. Changing the method and norm didn’t help with this problem. My only guess is that because the chords aren’t played by a conventional piano sound, the algorithm struggles with filling in which chord it is. However, all this is a very interesting problem to think about.